Decoding Age-specific Changes in Brain Functional Connectivity Using a Sliding-window Based Clustering Method
Zhang, A.; Pagliaccio, D.; Marsh, R.; Lee, S.
Show abstract
Functional magnetic resonance imaging (fMRI) permits detailed study of human brain function. Understanding the age-specific development of neural circuits in the typically developing brain may help us generate new hypotheses for developmental psychopathologies. Functional connectivity (FC), defined as the statistical associations between two brain regions, has been widely used in estimating functional networks from fMRI data. Previous research has shown that the evolution of FC does not follow a linear trend, particularly from childhood to young adulthood. Thus, this work aims to detect the nuanced FC changes with age from the non-linear curves and identify age-period-specific FC development patterns. We proposed a sliding-window based clustering approach to identify refined age interval of FC development. We used resting-state fMRI (rs-fMRI) data from the human connectome project-development (HCP-D), which recruited children, adolescents, and young adults aged from 5 to 21 years. Our analyses revealed different developmental patterns of resting-state FC by sex. In general, females matured earlier than males, but males had a faster development rate during age 100 -120 months. We identified four developmental phases: network construction in late childhood, segregation and integration construction in adolescence, network pruning in young adulthood, and a unique phase in males -- U-shape development. In addition, we investigated the sex effect on the slopes of FC-age correlation. Males had higher slopes during late childhood and young adulthood. These results inform trajectories of normal FC development, information that can in the future be used to pinpoint when development might go awry in neurodevelopmental disorders. HighlightO_LIPropose a novel sliding-window-based framework to identify refined age intervals of functional connectivity (FC) development. C_LIO_LIIdentify four developmental phases: network construction in late childhood, segregation and integration in adolescence, network pruning in young adulthood, and a unique phase in males -- U-shape development. C_LIO_LICharacterize the representative FC pattern for each developmental phase based on global network statistics, modular connectivity, and hub ROIs. C_LIO_LIReveal sex differences in developmental timing, rate, and patterns of resting-state FC. C_LI
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Enhancing Prediction of Human Traits and Behaviors through Ensemble Learning of Traditional and Novel Resting-State fMRI Connectivity Analyses 96%
- Edge-centric analysis of time-varying functional brain networks with applications in autism spectrum disorder 95%
- The overlapping modular organization of human brain functional networks across the adult lifespan 95%
Similar papers in this journal
- Age-related changes in the motor planning strategy slow down motor initiation in elderly adults 95%
- Personalized models of Disorders of Consciousness revealcomplementary roles of connectivity and local parameters in diagnosis and prognosis 94%
- Eigenvector alignment: assessing functional network changes in amnestic mild cognitive impairment and Alzheimer's disease 94%
Similar papers in this journal
Similar papers in this journal
- Resting-state fMRI data of awake dogs (Canis familiaris) via group-level independent component analysis reveal multiple, spatially distributed resting-state networks 94%
- Impact of meningioma and glioma on whole-brain dynamics 94%
- Measuring Robustness of Brain Networks in Autism Spectrum Disorder with Ricci Curvature 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.